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Xiaotian Dai

Assistant Professor
Mathematics
  • About
  • Awards & Honors
  • Research

Current Courses

499.004Independent Research For The Master's Thesis

453.001Regression Analysis

Research Interests & Areas

My research interests are in developing new statistical methods for high-throughput and complex genomic, transcriptomic, and epidemiologic data. I have been broadly interested in Bayesian statistical methods, high-dimensional data variable selection, functional data analysis, and other statistics/biostatistics areas.

IMS New Researcher Travel Award

Institute of Mathematical Statistics
2024

Journal Article

Dai, X., Acosta, N., Lu, X., et al (2024). A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater. Statistics in Medicine, 43(6): 1153-1169.
Dai, X., Lu, X., & Chekouo, T. (2023). A Bayesian genomic selection approach incorporating prior feature ordering and population structures with application to coronary artery disease.
Statistical Methods in Medical Research, 32(8): 1616-1629.

Grants & Contracts

Advancing Predictive Models with SDOH Integration in Healthcare. Connected Communities Initiative (OSF HealthCare and ISU). Local. (2024)